Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
Both approaches identified hemoglobin as one of the most significant predictors of CKD risk. Additional top-ranked features included blood urea, sodium levels, red blood cell count, potassium, and ...
Machine learning enhances proteomics by optimizing peptide identification, structure prediction, and biomarker discovery.
Read more about From disease detection to biomass forecasting: AI improves aquaculture risk strategy on Devdiscourse ...
Objective Cardiovascular diseases (CVD) remain the leading cause of mortality globally, necessitating early risk identification to improve prevention and management strategies. Traditional risk ...
1 Department of Cardiology, Liuzhou People’s Hospital, Affiliated of Guangxi Medical University, Liuzhou, Guangxi, China 2 The Key Laboratory of Coronary Atherosclerotic Disease Prevention and ...
Alterations in brain structure have been suggested to be associated with bulimia nervosa (BN). This study aimed to employ machine learning (ML) methods based on diffusion tensor imaging (DTI) to ...
ABSTRACT: Credit risk assessment plays an important role in financial services by estimating the chance of a borrower defaulting. Recently, although the Large Language Models (LLMs) have demonstrated ...
A brain-computer interface (BCI) system enables direct communication between the brain and external devices, offering significant potential for assistive technologies and advanced human-computer ...
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